Gofore Oyj (GOFORE) Earnings Call Transcript & Summary

Good morning, everyone and welcome to Intelligent Industry 2024. Now take a moment to find your seat, you're in no hurry. I know the breakfast was super good. At least my breakfast doesn't normally look like that. So make the most of it. And then just slowly make your way here. There's plenty of seats also here in the front. So I'm sure there's room for everyone. Intelligent Industry 2024 event takes place in its -- this format for the first time. The event was previously known as Change. So I'm very happy that today, we get to dive into the industrial market and the topics that are relevant to the industrial customers in a little bit more detail. Now this is also the first time we are here in Siltasaari, which is amazing because this will be the location of Helsinki office -- Gofore's Helsinki office starting from the beginning of next year. So we're also doing kind of a test run on these facilities. My name is Outi Maatta, and I work with our industrial customers at Gofore. The clicker, let's see. Here is the agenda. So we will be covering three topics today. We'll start the morning by diving deep into AI, a super hot topic for everyone, I'm sure. And here to discuss the topic is Karoliina Partanen and Henrik Vuoksenmaa. After this, we will move on to a keynote speech by Tomio Pihkala from KONE's about accelerating digitally enabled services. Then we will have a short break, time to stretch your legs and get some coffee, and we will end the day with a panel discussion about how do we make sense out of EU regulation? And how do we turn them into concrete actions and hopefully, even some opportunities that may lie in them. And we have an amazing array of panelists. We have Anna Nicol from Fazer, Eeva Impio-Loimaala from Metsa Board, Karoliina Partanen doing an encore and then also Gofore's Markus Asikainen. Now I hope that after the show and during the break, you take a moment to exchange some ideas and thoughts with the amazing people that we have here and the new friends that you are sure to make during the day. And yes, we hope that you are also like very actively taking part in the discussion. We also have about 150 people following the stream online. So very happy to have all of you with us as well today. And I hope that you also participate, for example, using a chat function that we have. So take a moment please and scan this QR code. You find it also on those paper triangles that you have on the tables because you will need this later. This is your way of asking questions from the audience, but also there will be a couple of polls that I hope that everyone answers and they will also pop up during -- from the same link. So it's a good idea to open that already now. And please be active. Good. But I think we are ready for our first show. So welcome. Key findings of a new study, AI and competitiveness of industrial companies. So Gofore conducted over the summer a research among manufacturing organizations in Finland. And indeed, the questions were around how do they believe that they will benefit from AI, Karoliina Partanen comes from AI Finland, which is a network under Finnish technology industries with the purpose of promoting the adoption and benefits coming from AI. And Henrik Vuoksenmaa is the person behind this research. So he has all the knowledge and insight of the interviews. So thank you. Let's get started. Now we approached the topic so that we at Gofore, of course, talk to a lot of our customers. We talk to our partners and we talk about things that are happening in the market. And then there are some things that we hear a little bit more often than other things. And particularly with AI, everyone seems to have an opinion, and everyone has some kind of an experience or something similar. So we have put together some statements that we now hope Karoliina and Henrik will comment. And I want to also highlight that these are not Gofore's opinions, but these are something that we have been hearing from the market. So let's start with the first one. The market and the way organizations operate will be revolutionized in the next 5 years, thanks to AI.

If I may start, I totally agree with this statement. We have a couple of examples. For instance, Tesla and Apple will launch a couple of products in any day now that will entirely change the way we think, both cars and mobile phones right now. And the challenge is that the product development and R&D that other companies are doing is not visible for the clients or competitors. But do you think that there is nothing really happening but in reality, there has been some R&D projects going on for years. And in the case of Tesla, they are launching self-driving taxi now in October, and that will entirely disrupt the car industry. Who wants to spend time on driving when you can watch Netflix or do work or really anything while the car is driving itself. And then again, for mobile phones, Apple is -- has been working really hard to have very well-working audio comments for the phone so you no longer have to be typing as a real boomer when you can simply just comment by speaking by audio, so who wants to buy a phone where you need to be using this actual device when you can only use your glasses or your earplugs and command and find the information you need by speaking.

Okay. If we think from the perspective of the manufacturing industry leaders, we interviewed 13 of them from rather big companies working in Finland. It was evident that there's going to be a revolution. But when that's a different question. We asked from -- on a scale from 1 to 5. I think we have a slide for that there as well about how much they believe that AI solutions will affect their marketing -- the market competition situation in the next 2 years or 10 years, 5 obviously falls there in between. But I think the general sentiment was very much that there will be a revolution, but not just yet. So it's an industry that's moving quite slowly changing slowly. In 10 years, that's a big thing. But I think the general sentiment was that nobody is really doing anything radical yet. They're preparing, getting their data set, getting people to learn about AI, doing the first concrete projects, for example. But 5 years, that's, I think -- if I would ask again now some of the people who I interviewed, I think they would disagree that the revolution would be in 5 years.

Thank you. Now I think another thing that we see probably all of us kind of see this sentiment that organizations are in a rush to somehow win in AI. What do you think?

Well, if I continue from that, I think the approach was way more cautious than rush. I didn't feel that's kind of rush from their -- there is a rush to do something, but I don't think there was a rush to do big things immediately. I think a quite general approach was to maybe take a step aside, get kind of learn and see what others are doing. There were discussions that, "do I want to be the first one? Or do I want to be kind of the second one who then reaps the low-hanging fruits when somebody else has done the heavy lifting". I think it was interesting approach that one as well.

Yes. To build on that, I think that is so worrying because companies in Sweden, everywhere in Europe, not to mention China and America, they are in a hurry, and they can actually steal all our business. There is 13 billion new money coming to AI industries and 70, not 17, but 70 percentage of that is about to go to China and America if we don't change our strategy and become more active in doing R&D in terms of AI. And I think it's crazy. No company in this world is going to wait 1 or 2 years and stop their normal R&D. So why would you -- sorry -- so why would you wait with AI, which is changing even more quickly than your ordinary R&D technologies. So I think AI should be part of your normal strategy, your normal product development and your innovation processes, although I believe, quite a many companies do not have innovation processes, which is part of the problem.

If I can elaborate on that. What was interesting also was that the visions about how AI will change the industry. They already are there. So basically, I think many of the interviewees they said that they have ideas how things could look like in 10 years, but still very few actually did some big moves to reach those goals.

Yes. I believe there was a mention that nobody really wants to be the pioneer in this and which is what causes concern. Good. And hey, feel free to comment on these statements, please also on the chat. I can see that how much action is going on here. The third statement AI experiments have not brought real benefits. What are your thoughts on this?

Okay. If I may start now. Well, if we start from generative AI, I don't think there is any consultancy or a law firm or any like real knowledge-intensive company right now that is not using generative AI, so I think that the benefits are very visible in that field. But when we think about industrial companies and for instance, manufacturing, the benefits won't come from generative AI, but they come from these more traditional AI technologies, such as automation, robotics, predictive maintenance, machine learning, machine vision and so on. And there has been so many innovations in that field over the past 15 years. So I think this is not right.

Yes. I would say that the companies we interviewed would say yes and no. So the first trials, first projects they have done often quite small. But there have been some kind of progress, some kind of successes that give them confidence that, okay, this might be a real thing. They might predict customer demand, they might put their user manuals, or customer supports to GenAI things and so on. But then when we're talking about the revolution, it's still very small. So I think none of the 13 interviewed leaders told we're kind of super proud about any individual innovation that would really have changed their business, for example.

I think that's only the nature of Finnish people, because I was last week in a panel with Sandvik. And is there somebody from Sandvik by the way? Because they have been doing 10 years really hard work to digitalize their whole data, and they are still very modest saying that, "Oh we are only in starting our AI way," but their huge devices worth millions working on the ground. They are already totally autonomous. And that's actually based on AI. So I think there has already been pretty huge benefits seen in large enterprises, but companies don't necessarily realize it's -- thanks to AI.

And it's probably a matter also of what our people are really expecting. But then I also see there being a little bit of a conflict if no one really wants to be a pioneer and try something big necessarily, but then still hoping to get something big. So thank you. Maybe following the previous statement, another statement that has been recently heard a few times more often than earlier was that AI's biggest benefit is actually predictability and foresight.

I think from the projects that we have mentioned in the interviews, predictability was quite common, not only predictability of their own work, but enabling more predictability for the customers. So when we're talking about let's say, machinery, letting the customer understand whether how their things will work in the future as well. But then if we go back to the GenAI side, I think there, the dream is kind of how this robot friend, coworker who, again, does the heavy lifting, doesn't have to -- takes the boring parts of -- from the job, and also the same in the factory side, I think kind of make work more human maybe it could be one way to say it as well.

Yes. Of course, predictability is huge. For instance, KONE's entire business is based on that 24/7 predictability service or predictive maintenance service. But I wouldn't say it's the biggest and the only benefit, for instance, sustainability is rapidly growing topic or theme. And for instance, Mirka or Betolar, they are doing very inspiring work with robotics to increase their sustainability in their core products, which is sand paper and concrete.

Maybe if I could elaborate from the customer experience point of view, Also, it was evident that the companies have started more from their support functions, and they maybe feel that kind of the safer approach. I think the artificial intelligence is kind of, I would say, scary in a way. Do we really -- can we really give it that much kind of the -- if we deliver something with AI to the customer, how much can we trust in that? So that's why they started from the internal projects, which they always kind of had someone to overlook, but is it then revolutionary? That's the question.

Yes. Still one comment. Yes, that's a very good point because in Europe and in Finland, there is no tolerance for mistakes for obvious reasons, like safety. In China, there has been the self-driving cars for years, because for them, it's entirely tolerable if one person out of 1,000 or so get killed. So yes, I think it's very important that we have a high criteria here in Europe and Finland. And I believe we can still reach that level with AI.

Yes. Thank you. Now moving on to the next statement. AI strategy is not needed.

We had a question in the survey as well about if the companies had AI strategy. And 30 percentage of the interview is said that it's currently in development or just about to come or something like that. And I think some of the challenges that we found in the discussions kind of supported that, because very common, I would say, challenge was that the information doesn't really flow in the organizations if there's an innovation in one side of the organization, it might get kind of seal out. It doesn't go to the other side. They don't really know where they get support from -- they don't know what has already been learned in the organization and so on. So definitely, there is a need for some kind of shared knowledge, shared, I would say, rules in a way. But is it AI strategy? That's a different question again.

Yes. I agree with you. I think companies should rather have a good strategy enabled by AI or there should be AI governance model or good processes for collecting ideas from employees and prioritizing them because what the leading manufacturing companies are seeing or doing right now is that they want to collect ideas from the blue-collar workers because they are in the customer interface or they are in the production, and they actually know what the challenges or the bottlenecks are right now. So yes, I think there should be -- AI should be in the strategy, but there shouldn't be separate strategy, but they should all come together.

Thank you. Yes, you can see that 54% does not have one and 30% are developing it. Another question. Organizations do not know how to lead AI-powered operations.

Okay. I can start now. I think companies will know how to deliver this once they get their plan sorted out. I have great faith on our companies.

Yes. And I think the companies also have a very high level of confidence on that. This was also discussed in the interviews. And again, common sentiment from them was that if and when the bigger projects and initiatives, time for them comes, we are ready and we know how to do these kind of things, we have managed large change initiatives in the past as well. And actually, that's kind of also the explanation why they feel that the assessment very often was based on how they had done in the past. So now what will be seen in the next few years is that how different are AI-related change processes and so on. I think, for example, the innovations when there's something so kind of new and, I would say, unchartered as AI, it's possible that the change initiative is going to be different as well. So I hope for the best when the companies that have a lot of confidence, I obviously hope that they do well, but we will see.

Yes. And this is actually nothing new. When I started my career in 2010 at Nokia, innovation management was a big topic. And I think the big companies or enterprises at least already have those processes somewhere. Maybe they have forgotten them, but now it's time to like get them back from the dust.

Great. What do you think would be maybe the most important things that leaders should take with them to be able to better benefit the top tips.

I can start. I would pay more attention in the beginning of the process and think about what kind of ideas or concepts would bring the biggest benefit, because no matter what AI idea, you are about to take to production, the price tag will anyway be pretty big. So you should really carefully consider if you want to do that for like a small support process or something that will actually enhance your customer experience. I believe the customer experience end will bring your more competitive advantage.

Yes. I think the many popular things that the companies are doing right now is kind of learning AI getting whether AI capability, basically teaching everyone about what is AI and so on, also improving their data. A quite common approach was that just to do something, just to be sure that you don't waste time, now is a good time to kind of gather all kinds of data, have them in inform that makes sense in places that make sense because in the future, you might need that for AI. Personally, I think that the kind of innovation culture and how those innovations are kind of fostered in the organization, I think that must be kind of important things even if you don't want to kind of go all in on AI, I think that kind of...

That pays of...

Yes. Yes, it makes sense anyway. So yes.

What if someone now -- this is a bit of a bonus question. Someone at the audience is really feeling like, "Oh, we are lagging behind." What would be the first thing for them to do right now?

Of course, join AI Finland network. Sorry, I had to use that for once. Yes, because in our network, you will at least hear great inspirational use cases from other companies and other good choice would be to ask Gofore, what should we do.

Yes, I would call Outi definitely.

Okay, yes. Definitely.

Yes. Do something, it sounds stupid, but I think that do something is a good start, get the kind of real turning.

Yes. Thank you. Now once again, if you don't have the QR code open, you can ask some more questions via here, but I do have a couple from the audience. Let's start with this one. Do you have any case studies of AI in manufacturing industry demand, forecasting and planning?

Demand, forecasting and planning. I might have some. Yes. Is there a place to share links? I kind of remember URLs.

Yes. At least for me, this is something that I have been hearing and which kind of links back to the foresight and predictability in a way that this is what people would hope to achieve.

Yes. And that kind of project was mentioned in the interviews. They were obviously anonymous, but I can tell that has happened in Finland somewhere -- someone, somewhere.

Good. And then another question, interesting one, is AI transforming more the work of knowledge workers or industrial workers or process workers?

I have very clear answer here. I think generative AI will only be like supporting tool for knowledge workers. But unfortunately, for manufacturing workers, it will in some time, replace most of the workers.

Good. We hear already today that having excellent digital services is a must in being part of the game, and AI will surely be a building block in them. But how would you define AI in just one sentence?

I think it's the intelligent of machines and devices.

Sounds pretty good.

Thank you. If there are no hands raised or further questions in the chat, then I believe we give a warm thank you. Thank you, Henrik and Karoliina. Okay. So you will all receive this study research via e-mail, and it is also downloadable on Gofore's website. There's a lot more insights and findings and also these interesting pie charts, which, at least to me, are always the best part of any research. Now it's time for our keynote speech. So accelerating the digitally enabled services. And here to talk about the topic is Tomio Pihkala, welcome, Chief Technology Officer of KONE. And remember, you have again the possibility to ask questions by using the chat.

Well, thank you, and thank you for having me. Really great to be here. Actually, this is a perfect timing to come here because just 1.5 weeks ago, we launched our new strategy as a company. So actually, I can talk about things, which I had in my presentation. very interesting dialogue. It's good to see some kind of dialogue between more optimistic and a little bit more pessimistic view about AI. I'm -- actually I admit that I'm a more optimistic guy, but -- so my topic is accelerating digital enabled services. And this is actually part of bigger phenomenon which is happening across the industries where technologies -- new technologies, particularly AI are transforming industries and then, of course, you can decide whether you are in the driving seat or whether you can -- you just go with the flow. And my recommendation is to go to the driving seat. Well, let me first introduce KONE briefly. And it's always good to start with the purpose, why we exist, why we come to the office every morning, what is the deeper reason for company's existence. So let me show you a fresh video we just launched also 1.5 week ago which we're trying to kind of illustrate what we are trying to do. [Presentation]

We shape the future of cities. That is our purpose. And it's all about offering innovative and sustainable people flow solutions to our customers and users and really making sure that we -- in our own part, we can help to improve the flow of urban life. We are more than 100 years old company. We try to remind ourselves that we used to be a start-up company. And why, it's important to remind because we have to be agile and fast and also ambitious company. And that's why we are reminding about this story every now and then. We are supported by very favorable megatrends, urbanization. It's increasingly also urban renewal, not just new cities build in different part of the world. These are obviously creating huge opportunities for companies like KONE. Technological disruption and development is a big deal. If you think about IoT, Industrial Internet, we have a lot of equipments in our field. And when we are connecting them, when we are able to generate data, this data is actually very useful to help our customers to help to improve the service quality. And then, of course, when you have a lot of data, then AI will come to the picture. Sustainability, 40% of the global CO2 emissions happening in the buildings. So actually, if you want to solve the climate change, you have to do something for existing buildings. And we happen to be in the heart of the building. So we feel that we have important role to play. A few numbers about KONE. We are transporting 2 billion people every day. So that's how we are contributing to the mission and purpose. Elevators, escalators, people are using them a lot. We have EUR 11 billion revenue, out of which 60% is service amortization. And this is increasingly growing part of our business, which we are also very much put in our focus. We are serving 1.6 million assets in our maintenance field, and there are 60,000 employees, out of which 40,000 are field technicians, these blue color workers who are never in the office, who are always driving this van and you can see sometimes on the street. And we are serving 600,000 customers, a lot of small, medium-sized customers. KONE will not be a leading company in our industry without innovations. We have been able to demonstrate that we can disrupt the industry like elevator industry. And we have done it several times with many innovations. If you look at what has happened since 2014, '15, they actually shift towards the digital innovations. So more and more, we see that digital technologies are great enablers for innovations. And what are some of the technologies we are very much focusing on and investing and betting in are following. These are, we believe that are very relevant for our industry and also helping us to come up with a very innovative solution to our customers. And first is generative AI. We decided to take a pretty proactive stance here. bottom-up approach, we let everybody to come and join the community, and it has been quite an interesting phenomenon since then. Robotics and automation, because we are suffering a labor shortage in our industry. And it's going to get worse. We have to be able to automate. We have to be able to use robotics in our business. And then part of solving the climate change challenge and reducing carbon, you have to also invest in clean technology and new materials. And then this starting to immerse in reality. This is an area where I feel like the industry has not been yet mature to see the opportunity, but we believe that this will come also eventually. And then, of course, IoT and data analytics. So I'm really excited to tell today that we have launched our new strategy. Before introducing that strategy briefly, I would like to highlight some of the, let's say, elements in that strategy. First of all, ambitions. We had a new CEO who joined the company at the beginning of the year. And this was one of the first I think he started to challenge the theme that, "Hey, do we have high ambitions." Maybe we are a little bit too humble, honest Finnish company who tend to accept certain realities. So basically trying to go out of comfort zone. So try to set a target, which are inspiring but also challenge your existing way of working, challenge you to go out of comfort zone. And then strategic shift, these are the key focus areas which are enabling us to get to the ambitions. And then the core, which is about our people, how we work and how we serve and deliver to our customers. And this is the strategy. It's one pager. Everything is here. So there's nothing else. So our strategy title is rise to lead. And basically, we have said that now we are going to be a leader. We want to be a leader in -- be the #1 choice for employees and customers. Here, we have a good foundation. Actually, we have very highly engaged employees and also high customer satisfaction. We want to be a leader in innovation and sustainability. This was the one which caused a lot of discussion, can be really be so bold that we want to say that we are industry leader in innovation and sustainability, Yes, we want. And then want to also lead in growth and profitability. So basically increase the market share, outgrow the competition in a profitable way. And how do we get there? There are four strategic shifts actually digital, it's all about digitalizing and transforming our service business. Dry modernization. There are more than 11 million elevators, escalators, which are more than 15 years old. And we are just addressing a fraction of it. How do we really capture the big growth opportunity. This is the single biggest growth engine for our industry. Number three, win residential. Why? Because residential segment is the biggest segment in our industry. Housing -- affordable housing, all the building where you are living. They are full of elevators. And if you want to -- and to be competitive in residential segment means that you're also competitive in other segments because this is the most also a tough segment to win. And then cut carbon. This should be self-evident. It's about reducing carbon in Scope 1, Scope 3 and also -- Scope 3, which is the most difficult one. But do it in such a way that you will create a good business. And then core, which is kind of gluing and tying everything together is their core and the easiest to work for and work with. And then we have values as a foundational element. So this is our strategy. And today, I will actually dive into the one of the strategic shift: Accelerate Digital. So what is Accelerate Digital. We have been doing -- conducting elevator maintenance more or less in the same way past 100 years. And now basically, we are saying that next 5, 6 years, it's going to completely transform. Both statements, but there are some good grounding and reasoning for that. First of all, we have said in this strategy shift that we want to connect all our assets. Today, we have 33% of our elevators, escalators are connected to the IoT. We're going to say, we're going to connect the rest. Even those customers who don't even care about that, we were going to connect. And we'll figure out the way how we actually get the benefits out of it. Well, we basically decided to just connect, let's get the data. Let's start to figure out how do we use that to improve our business. Very important other objective is to really improve the daily life of our technicians. And these are our most valuable assets. And basically, we are saying that we have to become technician obsessed. Everything needs to start from the technicians who are never in the office, who are very difficult to even reach, but they are serving our customers. We have to provide solutions which are creating good experience for them so that we can create the pool, we can actually accelerate transformation, because if they don't believe in these solutions, it's very hard to actually transform. And then this more financial objective, but really grow 10% yearly in the service business. This is probably the most important business KPI our investors are looking, because this has -- it's our most profitable business for KONE. So this is -- these are the high-level OKRs for our share shift called Accelerate Digital. And we are basically saying that we are going to transform this business. But it's challenging. It's not easy. First of all, there are a lot of different kind of equipments, all the new elevators, escalators, building doors, hundreds of non-KONE elevators. We are -- actually half of our service base are our competitor agreements. How do you connect those? Then we have people, 40,000 people. Many of them are old people. They are soon retired. They -- it's not that easy to learn the new tricks. Then on the other hand, you need to attract the new talents, but -- young talents, but they are not necessarily so interested in working in this field. So quite a big task ahead. Now we are using AI to boost this transformation. It was mentioned in the opening session that we use in 24/7 Connected Services. This is our predictive maintenance solution, which we are already selling as a value offering we want to expand that. The beauty of that solution is that it will actually get better every day. When you get more data, when you improve your operative analytics, it just gets better. So that's something we are looking. We want to proactively identify up to 80% of failures and take preventive action so that customer doesn't even see that there was a problem in elevator. But then it's not only that. It's not just fixing the issues and preventing issues. But also when you then go to the site, we have a regular maintenance visits. How do you sort of deploy the right people and dispatch people in the right way. Here you can use AI? How do you then optimize the actual maintenance content based on the condition of the equipment, because we, of course, get a lot of data we know about these equipments in real time. So how do we optimize the visits, which you need to make. You can remove a lot of waste. You can improve productivity. And then GenAI is actually the one area where we see also use cases in -- for technician. We have launched technician assistant, which is something I will introduce briefly in a minute. A few more words about 24/7 Connected Services. What is cool about digital service, which you have the scale and which is approaching a big amount of users and customers, it just gets better because you get more data. Now what are the some of the value propositions which we are offering to our customers. First of all, it's about real-time information. And this is important for our customers because if you have a facility manager, you don't want to be the last person to know that your tenant is trapped in elevator. That's not very good for your business. You want to know if there is some problem, you want to also know that KONE is taking actions real time. You want immediate response. You want full transparency. And that was difficult in the beginning. How can we really -- I mean, if you provide a full transparency isn't that risky? Maybe customers see all our problems. Yes, I mean, full transparency. But it also forced us to improve. Number two, predictive maintenance, I already mentioned. So there's just so much opportunities to improve your machine learning algorithms and just the way how you use the -- apply the data. And then there is ice on the cake is that, yes, I mean, you can, of course, send technicians to do some of the fixes, but what if you don't have to send anybody. You just do the remotely everything. So we have exciting new use cases called remote services. I'll actually show one video in a minute. We are already in this journey. We see benefits coming out. So AI is bringing benefits in our case. So we have 400,000 elevators, escalators connected, and we have already able to decrease the call-outs so -- basically the failures of elevators by 40%. In this journey, we started this in 2015, so about 7 years ago. We have decreased entrapments. These are the most annoying type of failures. When you are trap in elevator, it's not very nice feeling. How many of you have been trapped in an elevator? Okay, I feel very sorry about that. I have some good news later on. I'll tell about that. Something good is coming. 70% of the faults are recognized in advance. This is a huge -- and this is the KPI which R&D guys are looking, and our CEO is also looking that we have to improve -- keep improving. Let me first show the first concrete use case, technicians assistant. It's actually pretty simple. I mean, most of you know about GenAI and what kind of things you can do with GenAI. Basically, they are -- basically, it's about helping technicians to fix the problems. And when there is a complicated technical issue, technician usually call their boss or maybe their colleague, "How do I fix this elevator? I don't know." Or they call so-called help desk, which is more official channel. And most of them will call help desk. Now we have all the manuals, all the documents. So we basically create a use case where GenAI will basically become your conversational interface. And we have now piloted this -- this was -- one of the beautiful thing is that it's actually very quick. It's actually very easy to implement this type of solution because you are using foundational models provided by the big companies. And we, of course, need to do a little bit of training and learning. But basically, we implemented this to the four front lines and the initial results, 44% of the cases where they usually would call to help desk the GenAI was able to solve the problem. So -- and these are -- these were actually mostly mature front clients where we have a lot of aging workforce. So think about it. Think about when you go to China or some of the markets where we have much more younger employees. So here is actually some video kind of going on. But basically, it is like using Chat GPT, similar things. You ask questions, and it will give you answers and also give you some links. Of course, there are some prompting, make it easy. You don't have to write. And then you can always then get the source information like manuals and so on. Simple like that, but very powerful. We think that this would probably bring EUR 30 million, EUR 40 million impact to the bottom line if we are scaling this. Not a bad use case. This is just a one. It took 6 months to do the POC. Remote services. Now when you have connected assets, when you have all these data flowing and when you already have analytics deployed, there's this magic what you can do, which is a remote service. Here's the video. [Presentation]

So one minute rescue. I think that will be much better than what you have experienced This, of course, requires a very good security and there are lot of regulations which you need to also consider in different countries. But this is something which is now coming. And of course, you can imagine what are the benefits -- not just for customers, but also in terms of productivity. All right. I'm actually coming to the end, and it's good to let me summarize some of the key learnings from our journey in terms of the service transformation and digital transformation. And these are just some of -- this is not fully comprehensive, but some of the key points which I wanted to highlight today for you guys. First of all, I'm not saying that we are perfect here. We actually have a lot of work to do in KONE, but you really need to put your user into the center, and I really mean it. We know this is not just talking, you have to actually -- and this is one of the hardest things actually to do. It probably requires a big cultural change in any company. But you need to develop digital solutions with your users from the beginning and for them. They have to be involved from the very, very beginning. This is key because otherwise, you don't create the pull. And if you don't create the pool, how can you force 40,000 technicians to change their behavior? Very, very difficult. They have to buy it. They have to want it. So that's #1. And that's not possible if your data platforms, your technology platforms, your product architecture or IT landscape is not sort of adjusted to create the better user experience. Then transformation is always leadership challenge. We are trying to change the behavior of people. You need leadership. You need the people who are showing the way, explaining why we have to do this and communicate, communicate, communicate, providing support and help and resources. This is not happening without investments. And then #3, how do we -- we need to have our courage to challenge existing business models and go-to-market models. 24/7 connected services, which are introduced, forced us to change the business model. So we are basically selling the outcome. We are not even -- we are not selling the hardware, which we also need if you want to connect equipment or we are selling this as a service. But now when we are saying that we have to connect 100% of our equipments, we most likely need to change business model again because, frankly, there are customers, who doesn't want to pay any euro extra because of our service, what we're offering. So you need to figure out other way to create the benefits. Have go-to-market models. I mentioned try monetization initiative briefly. If you want to tap the whole market of 11 million elevators, you have to find a different way to create the demand. And that's most likely done by digital means. So these are some of the key learnings. I hope that they are quite applicable for any of your transformations. So that's it. That's my picture of my presentation. And I don't know if there's any questions or comments.

Yes. Now it's a great time to send them over. I actually have a question. Well, first of all, thank you for the story, and it is indeed very inspiring to hear how you have succeeded also, let's say, on a larger scale, but then also getting 6-month fantastic benefits from AI. I think that's very great. But could you please tell us like what do you eat for breakfast? How do you make it happen? What is your secret sauce in your organization that you're actually able to do all that?

Company culture is something which doesn't change overnight. And I think we have built over the years and decades certain type of company culture, which will encourage innovations, for example. So you have a courage to fail. You have -- you can fail and you can try to do different things. But on the other hand, the culture is something you need to actively also develop. And so I think this is something where we are putting a lot of focus. So every strategy and even this strategy, we highlight a lot of values, which are important for the company. So that 60,000 employees would somehow, behave in a similar way because it's not enough that you have a couple of very innovative guys, but you want to make sure that your full employee base is driving to the same direction. And that requires our cultural development and I think there, the values are key. So we have 4 values. We have a customer, we have a care, we have a collaboration and courage. Now we, of course, measure also different ways how where we are, employee surveys, of course, one way. In every strategic period, you want to also really think about what are the areas where you need to improve, particularly now in the current phase of your company. And our conclusion is the theme was courage, courage. I mean, AI, I mean, this discussion in the morning is actually about courage. Do you have a courage to take a risk? Are you bold? Are you decisive? Or do we just follow what others are doing? So that is something we did -- we have to improve to be successful.

Yes. And that's also maybe something that in the market situation, which is probably challenging for everyone. In one way or another, it's important to find that. Thank you. Now let's see what we have from the audience. Well, there was a detailed question that if you have an 80% target for proactively finding faults. Where are you now currently?

That's a question which my boss is asking every day. Not very easy to answer in a simple way, but -- and of course, depending on the assets, if you have KONE elevator, you have better predictability than third-party, obviously, depending on how rich data you actually have because actually the more you have the data, more you can use find all kind of correlations and so on. So I mean, safe, maybe your estimate is that we are somewhere below 50% still. And we think that we can go 80%, after that will be difficult because there are just too much human behavior. And our customers are sometimes behaving in very weird ways, something that AI cannot tackle for us.

Good. Another question from the audience. Have you learned something surprising from the IoT data. So do you have -- no, I'm missing the words. Yes, have you found something in that?

Yes. Yes. I mean, I mean, just -- there's a lot of data, which doesn't make sense. I mean there's just a lot of noise in data. So actually, one of the key issues actually when you improve your machine learning algorithms is that you're able to eliminate noise. So they are all kind of behavior in the field, which about usually they are end users, who makes very difficult to understand in a laboratory, how -- what does it really mean this data. And so then I think we have taken the approach of basically just going there and understanding, asking from the customer, asking from the technician, what is really going on, is I said, this equipment is sending real data. And that's the way to sort of eliminate some of the noise. And yes, every day, some surprises. You can -- you cannot imagine what kind of things people are doing in elevator.

Well, I was just about to say that this will keep us all up tonight when we think about it. So we'll see. One more question before we have a break. Your great video made the obvious thing that what would you have -- like would you have an ambition to expand people flow to other areas than the current core business?

Yes. I think, if you think -- I think of our purpose and mission to shape the city -- future of cities and really improve the urban flow. Obviously, you cannot do that alone. So we very much believe in the partnership and ecosystems. You need to build around some of the big problems like climate change is about -- for example, we just -- we are planning to launch a new ecosystem around modernizing equipment and we're going to invite a lot of companies across the Europe, and we also get some support from the government and so on. So I think, it's go more towards sort of partnership and rather than unnecessarily going beyond your scope.

Great. I believe this is it from the questions and feel free to continue now during the break, which we will have for about 15 minutes. So let's stretch our legs and get some more coffee and be back in a moment because we have the final great session coming up. But hey, warm thanks to Tomio. Fantastic speech. [Break]

Welcome back, everyone. I would ask you to please start making your way back to your seat. I'm sorry to interrupt your discussions, which I hear have been very good, and there has been a lot of things about the inspirational speeches of the morning. And I did hear via the coffee machine that there are some thoughts that people have gained during the morning. [indiscernible]. Okay. That's the Karoliina's microphone, I think. All right. Welcome back. We have had a great start to the morning. So we started up by having a look at AI. We had a little bit of a glimpse of an AI study that Gofore conducted over the summer that you will all receive later on. Then I think that no one was left cold after the fantastic presentation by Tomio, from KONE. And hopefully, you all got some ideas. And I think that the one word that could be described or something that everyone should at least remember from these sessions would be courage. And I really like that word, and I've noticed that I used it a lot myself as well. So let's all use it, makes even more impact. But hey, let's keep the chat open because we have, again, a fantastic opportunity to ask questions from people, who really know what they are talking about. So we are now continuing with a panel discussion around the topic of making sense of EU regulation. And now we are not going to talk about the regulation content in itself, but we are going to talk about the practical side of things and about how regulation can even perhaps bring some business opportunities, how amazing. And here to talk about the topic. We have a fantastic array of panelists. We have Anna Nicol, Director, Sustainability Strategy & Reporting at Fazer; then Eeva Impiö-Loimaala, General Counsel at Metsä Board; making an encore with us today, Karoliina Partanen, from Technology Industries of Finland or AI Finland; and Markus Asikainen, Head of Cybersecurity business at Gofore. So let's get going, and please also remember to ask questions. Now we all know that regulations may cause some headache and definitely, they cause some work in organizations. There are, of course, the threat of fines and penalties that you may have to deal with. And there are also costs related to compliance. And it's clear that a lot of effort needs to be put into understanding, interpreting and applying those regulations into your business. And we want to understand that whether this is something that can slow down innovation even? Or could it be something that is actually pushing us to do something that was earlier considered impossible? Good. So currently, we talk about, like the buzz around the regulations is we hear about and we talk about, for example, NIS2, EUDR, CSRD, Data Act, AI Act, and those were just a few. There are a lot more, trust me. But hey, panelists, are you ready?

Yes.

Good. I have a very small first question for you, which is that how do your organizations manage the amount of regulations? Maybe we can start with Anna.

We have project teams for the key regulations, and we are running those with kind of a steady project management with the leader and the steering group and trying to involve as many people as possible from the organization because they are the best who know what do we do and how do we need to develop. So I think that's the key. Structure and having a lot of people involved.

Yes.

And we have sort of the same kind of approach. But as a large company, Metsä Board and being even a part of even a larger group of companies, Metsä Group, we actually have a few functions that follow what's going on in the regulation scene. We have a corporate affairs team. They have team members in several countries and team in Brussels as well in the very core of the place, where the EU regulation is created. And of course, with lawyers and compliance function, we do follow what's going on. And when it's tend to implement something, we create a group or a project, whatever is needed in that purpose, a very similar approach.

Good. Thank you. Go ahead.

And we are actually building tools for companies to make it easier to understand the practicalities of all these new legislations with [ Citra ] and technology industries of Finland. And clearly, AI Finland, we are building a tool to -- where you can actually submit what you are about to do, and it will explain you what does a GDPR, AI Act, Data Act and all these different regulations, whether the -- what do you need to do to be compliant and what are the reporting needs and so on. And also, we are collecting these -- what is this term in English [Foreign Language]. Interpretations, yes. So we are collecting a library of those, now that AI Act and Data Act are still pretty new. It might be useful to hear from other companies, what are these interpretations in their cases.

Yes. I think that's a really important part of the implementation that you understand what is the actual kind of industry benchmark, if you're referring to that, so it's really good to hear that there are also technical solutions coming for helping companies with that.

Fantastic. Yes. Great. You explained, I think that you are probably leaders in a way how you handle these kind of topics and regulations and such and leading thinkers as well. But I want to ask you a little bit more specifically that how would you describe the role of top management when it comes to the regulations and their implementation?

Should I start again? Well, of course, we need the support from them. They need to be interested. They need to understand what is their role and responsibility in all of this, and they need to ensure that we have the resources. And at least in our company, we have regular ESG steering groups, where the top management and the top business leaders are monitoring that how we are dealing with this project. So they need to show their interest and maybe even a little bit nudging to the right direction and ensuring that the things are moving ahead.

Again, we have a very similar approach, but what I would like to highlight here, that the role of the top management is very essential. And it's not only about the rules and new regulations. It's about high ethical standards. And if you want to be a forerunner in something, you really need to have ambitious targets. And leading by example, it might be a cliche, but that's really crucial.

Do you have something to complement?

Yes. I think the situation awareness is one key word for top management. So you have to be able to kind of understand what kind of impact regulation will bring to your organization and, of course, the sponsorship and accountability that was mentioned here is crucial for success. Of course, you can outsource the actual implementation to the other kind of parts of organization. But at the end of the day, top management is always responsible and should be aware that what is the actual maturity when you are developing your organization towards regulation.

Now we actually have a question for the audience. you should get it via the link, the QR code link. So is top management involved and active regarding regulation implementation in your organization?

I'll start. It's nice to say that, yes. Of course, the CEO of Gofore is here. But to be honest, it's really nice to see that our top management has taken -- for example, NIS2 seriously for the day 1. So it's really nice to see that we can do it together. This kind of quite big rehearsal, it kind of impacts different places in the organization.

Yes. I believe this NIS2 is a great example where you really have to take a holistic approach about the implementation part of it. Good. Now let's see later what kind of replies we get from the audience for that question. I have another question for the panelists. And now I would really like you to kind of think about it from a very concrete way and kind of looking back at the maybe challenges that you had earlier. What would you say is the most difficult thing, when implementing a new regulation in your organization?

Maybe I can start now. And I would love to give a one-word answer here. But as a lawyer, I think it's not possible. But quite often, the most difficult part is that you have a new regulation tax that is maybe a bit too vague. You're not sure how to interpret it. And in different countries, it might have very different kinds of implications. And if you are a multinational company, you might be in the trouble finding out what's needed in different countries. But very often, it's related to what to do, what is expected. Many people spending an awful lot of time on thinking what is actually required. So that is probably the most difficult thing at least for us.

Yes, we are in the middle of the EUDR implementation. And like many of you probably have heard that EU made suggest and to postpone the implementation by 1 year last week. And like us and many other companies, we have been working on already for more than a year to be ready for this law, which was supposed to be enforced end of this year. And like Eeva said, it was not very well instructed that what is expected from the companies and a lot of different interpretations in the market. And still last week, we were thinking that we need to have this everything done and ready by end of this year. So it was a big relief that we have now 1 more year time. And EU also gave some instructions now how the law should be interpreted. So it is really a good thing. Of course, we need to make sure that these actions and the frustration and all these actions are going forward in full speed, but this reporting side, it's good that now there is 1 more year time, but still kind of an example that very difficult to implement a law when everyone who is reading is reading it in a little bit different way.

And as we discussed earlier, you mentioned that it actually posed a business risk as well because you don't really know what's going to happen?

Yes, certainly. So -- and also globally, some challenges we're seeing that the company is importing raw materials to Europe, we are also a little bit hesitant what they should do. And I think it was good that there is no time to react.

Based on my experience, the situation is pretty polarized according to the size of the company. Clearly, enterprises, do have their own law departments and in-house stuff. But I feel so sorry for all the SMEs who don't even have own lawyers, and they should now do all the same work than you are doing in a way bigger organizations. And according to my experience, actually quite many enterprises have done their homework pretty well, and you might even be compliant by nature because you have been building it for years already. But for SMEs, who are only now starting, it might be very hard.

I have to thank you, ETL at least in food industry, they are doing excellent work reviewing what laws are in coming and giving webinars to their network. So that certainly helps the smaller customers, who don't have the legal departments to review.

No, sorry, what was that again?

ETL [indiscernible].

Yes. The SMEs is really little tough one because the majority of organizations and companies varies a lot. So -- and at least in the cyber regulation, there are also overlapping acts and different kind of other guidelines. So the companies are struggling at that is this applicable for us? And also because there is overlapping there, not kind of see that what is the actual way to be compliant. So they are struggling with is this [ ISO 27000 ] ISMS, information security management system. Is this enough or kind of fulfilling that requirements and so on. So there's lots of kind of need for different kind of synthesis or analysis in the organization. And at the end of the day, it's kind of a matter of how the kind of understand your own capabilities in your organizations because at the end of the day, we always kind of should think that we are developing our capabilities and then what kind of capabilities the regulator is kind of waiting to be improved.

Yes. Would you be able to tell maybe some concrete example from your past where you have maybe come or overcome a challenge?

Well, for example, talking about the CSRD. This year would be the first year, when we should give the report. Of course, the report will begin next year. But last year, we thought that, okay, it's coming, let's get prepared and our annual report, which was published this year regarding 2023 was actually made, so that it follows the requirements of the new regulations. So we had to work a bit harder last year. But this year, it's of course, a bit easier, and it feels good that we did the hard work last year, and it now pays off.

Yes. Thanks for doing it. Everyone is monitoring your report.

I've heard that.

I think someone has to be the pioneer here as well so... And of course, regarding CSRD, we have 1 more year time. We are not listed companies, but family-owned company, so we can still use your last year report and a lot of the reports, who are published -- or which will be published early next year, and they could take a step back and look what the others are doing before we publish our own one. Good. We have actually another question for the audience coming up on your phones, which is that have your organizations been struggling or succeeding with the implementation? So take a moment to think about that while we go ahead with the panel, and please reply. Great. But hey, now let's look at the positive side of things. There are those as well. What possibilities do regulation bring to businesses? I think at least the EUDR now, it's forcing really the whole industry to develop the traceability of data. We will see the whole value chain all the way from the field to the consumer, and need to follow the origin of the raw material. And I really see the EUDR implementation as ICT project, and it's kind of a pilot, which will then probably provide a platform that we can build also the other sustainability data that we, for example, Scope 3 and we don't have the facts all the way from the start of the value chain and capable of reporting those. It's very difficult to report your SPT targets and do that. So I think it's -- in a way, it's a good pilot for that.

Yes. For IT companies, for example, I think the new regulations bring a lot of chances as well as the consultants on how to interpret it. The different kind of texts. But for example, for us, that's a bit more traditional field of the industry, for us industry. I would say that, of course, the new regulations force companies to have a critical look on what we are doing. Is there something we can do better transparency, things like that. And of course, when you are well prepared, it can give you a competitive advantage. If you do your homework properly. And in that way, you can probably help your clients, and that's what we are doing a lot. So how to -- for example, what is required, what the clients also need to do and so on. So it's also definitely a possibility.

And certainly, CSRD then is bringing the companies the same way of reporting on sustainability. So for the customers and for the investors and everyone, it is making sure that the ones who are actually doing the work properly that it will also show in the reports because those will be assured and made sure that the companies are reporting in the same way.

Yes, I agree. The possibilities are probably the biggest for consultancies. For instance, I just heard that a listed company, a global one, they made data governance project and the price tag was EUR 3 million. It took 3 years and 1,800 people to do all that. But I don't think that's really feasible. We must be seeing some new ways of doing that, productizing it, commercializing this kind of process and maybe doing it in a more innovative way. And also the big tech giants are bringing new tools in a market to streamline the data governance like fabric from Microsoft and so on. So hopefully, we will be seeing also new innovative start-ups doing this in a faster and efficient way.

I think end of the day, the business is all about the trust. So everything that's kind of increases the trust is good for business. And especially from the cyber and security perspective, I would say that, that kind of investment for developing your resilience is always a good investment for your business. It's a brand issue everyone wants to play with you when you are kind of considered to be trust partner. And of course, this is also covering your supply chains, which is quite a big topic in the NIS2 at the moment. So how to ensure that those partners that you are playing with are actually secured and now their kind of own responsibility for building that resilience.

Very good insights. There is another question again for the audience. I'm going to keep you in your toes on this one. So the question for you now is that for your organization, do you see regulations as a possibility or a threat? So take a moment to think about it. I think that probably people who like believe in certain things and so forth can utilize these regulations also as a push for organizations to finally do something and maybe do the extra work and put in the extra effort and walk the extra mile to really operate in the way that they should.

Totally.

Good I have a question maybe now time to bring all those practical tips and hints for the audience, again, to the table that what is maybe that one thing that organizations should pay attention to during the rest of the year?

Keep eyes open what the new parliament is starting to work on in the EU to get the insight for maybe what is the tone going forward. And at least for us, it's now how to use the extra time for the EUDR that, of course, we will continue. But time frame is a bit different.

Maybe the stress level went down a little.

A little bit, yes. So -- and then, of course, on merchandise, EUDR and the CSRD. So it's really kind of a prepare for next year when we need to be then applying for that.

Yes. I can maybe mention that the regulations that Anna and we're talking about. The tail. And I'm talking about the tail because the new parliament or the commission has indicated that they will give us a small break, which would be very much appreciated as for the regulation, but the tail is still there. So make sure that you have the resources that are needed for the implementation. So if they're not there yet, you still have the rest of the year time to start recruiting and building systems.

Yes, I think that was one of the things we talked about earlier as well that it typically is not the workload you expected it to be, but much more because there might be things that you discover along the way and some surprises always happen always. Yes. So better to be safe than sorry in that one as well.

Take care of the cyber risk management. That's the part of everything. I'm talking about digital resilience.

And I would say I get started with the data digitalization. It won't get easier.

Yes. Well, maybe before I jump into the audience questions, I still had one more kind of thought on my mind related to. You said earlier in the beginning of the panel discussions that you typically establish a project organization of a sort that then will help understand and implement the regulation. What kind of roles do you typically involve in these project organizations?

It very much depends on the regulation that is being implemented the relevant people from relevant functions. So, if it's mainly reporting, then it's maybe much more sustainability colleagues involved, of course, always management is being involved. And sometimes, we need people from the sales, sometimes from the wood procurement, it really depends on project.

Yes. Same with us. And regarding now our sustainability reporting, for example, has been fully led by the sustainability team so far. But now with the CSRD, we are getting our finance colleagues more and more involved in taking the responsibility, which is very good. But then there are also business-specific differences that EUDR for us is a confectionery headache. It doesn't involve that much other businesses. But for confectionery through coco and chocolate, it's a really critical project. So that is small at -- in 1 business.

I think there's no one preference as we hear here. But I think the planning is something that you have to do properly every time. So you have to kind of understand where you want to impact when you're implementing the new regulation, and it depends who are the actual accountable in the -- for example, in businesses.

Yes. And probably ICT is always some or involved because it's a good enabler there.Yes. It's a good enabler there.

Great. Now I'm going to have a look at the audience questions. There was actually already 1 earlier, and I saved it for you. What do you think about the EU AI Data Act? Will it help boost EU AI adoption or retarget?

AI or Data Act?

AI Act.

There's -- it says AI Data Act, but in my opinion, there's an AI Act and a Data Act.

If not, your opinion.

That was my understanding. You can comment on both.

Yes. Well, if I start from AI Act, it's causing a lot of troubles for many industries, especially health care. But I would say that lucky for industrial companies, it's actually not that demanding because most of the use cases will go to the low-risk category. Do you agree? Yes, especially in core business processes, it's, of course, different for support processes like HR or maybe finance. But in general, industrial companies in their core processes, they are safe according to AI Act. But if I have understood correctly, GDPR is a question mark here because if you have any personal data in your data sets, then you need to take GDPR into account, and that makes it very complex in every use case.

So Karoliina, there's a direct question to you as well that is there also a regulatory interpretation and impact guide for the sustainability area prepared by maybe [indiscernible] or AI Finland?

Yes. We have something like that cooking.

Good. So very beneficial things coming for all of you. Any further questions from the audience for our fantastic panelists? You can also raise your hand and speak up. I hope that you kind of maybe some for the key takeaways from this discussion would be that prepare, understand the reasoning behind the regulations and what is really the purpose of -- of why they are coming so that you get the better hang of the implementation as well and then prepare with sufficient resources and engage the right people in your organizations to make it happen. Any other maybe final last words that you would like to say to anyone listening? If not, then I would suggest that we thank you for your efforts. And feel free to continue the discussion also with our panelists. Now our event is coming to an end, but I hope that -- well, let's say, that the event program is coming to an end because I encourage you to still hang around for a while and really exchange your ideas and thoughts and reflect on what you have heard and maybe what is that something that you want to take with you when you return to the office. And also, there is still -- I was told, a lot of food back there, and it was pretty good. So I hope that you all have a second round of something to eat. And without further ado, I really, really want to thank you all for participating. And hopefully, we will see each other soon again. Thank you.